Yazar "Kus, Coskun" seçeneğine göre listele

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    The Beta Moyal-Slash Distribution
    (Selçuk Üniversitesi, 2014) Genc, Ali Alper; Korkmaz, Mustafa Cagatay; Kus, Coskun
    In this paper, we introduce a generalization of the Moyal distribution via the beta-Moyal distribution. We define the new distribution by relation of a beta-Moyal random variable with respect to a power of a uniform random variable as ordinary slash distribution definition. The newly defined distribution generalizes the Moyal and beta-Moyal distributions and is more flexible in terms of its kurtosis and skewness than the Moyal distribution. Basic properties of the new distribution are studied. We derive the maximum likelihood estimators of its parameters and apply the distribution to a real data set.
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    Estimation for the parameters of the Pareto distribution under progressive censoring
    (TAYLOR & FRANCIS INC, 2007) Kus, Coskun; Kaya, Mehmet F.
    In this article, progressive Type-II right censored sample from Pareto distribution is considered. Exact confidence region is derived for the parameters of the corresponding distribution under progressive censoring. Simulation study is performed to investigate the coverage probabilities of the proposed confidence region. Illustrative example is also given.
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    A new lifetime distribution
    (ELSEVIER SCIENCE BV, 2007) Kus, Coskun
    A new two-parameter distribution with decreasing failure rate is introduced. Various properties of the introduced distribution are discussed. The EM algorithm is used to determine the maximum likelihood estimates and the asymptotic variances and covariance of these estimates are obtained. Simulation studies are performed in order to assess the accuracy of the approximation of the variances and covariance of the maximum likelihood estimates and investigate the convergence of the proposed EM scheme. Illustrative examples based on real data are also given. (c) 2006 Elsevier B.V. All rights reserved.
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    On estimation based on progressive first-failure-censored sampling
    (ELSEVIER SCIENCE BV, 2009) Wu, Shuo-Jye; Kus, Coskun
    In this paper, a new life test plan called a progressive first-failure-censoring scheme is introduced. Maximum likelihood estimates, exact and approximate confidence intervals and an exact confidence region for the parameters of the Weibull distribution are discussed for the new censoring scheme. A numerical example is provided to illustrate the proposed censoring scheme. Some simulation results are presented and used to assess the performance of the proposed estimation methods developed here. The expected time required to complete the proposed life test plan is derived. Finally, a numerical study for comparing among different censoring schemes in terms of expected test time is given. (C) 2009 Elsevier B.V. All rights reserved.
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    Optimal experimental plan for multi-level stress testing with Weibull regression under progressive Type-II extremal censoring
    (TAYLOR & FRANCIS INC, 2017) Ng, Hon Keung Tony; Kinaci, Ismail; Kus, Coskun; Chan, Ping Shing
    In the design of constant-stress life-testing experiments, the optimal allocation in a multi-level stress test with Type-I or Type-II censoring based on the Weibull regression model has been studied in the literature. Conventional Type-I and Type-II censoring schemes restrict our ability to observe extreme failures in the experiment and these extreme failures are important in the estimation of upper quantiles and understanding of the tail behaviors of the lifetime distribution. For this reason, we propose the use of progressive extremal censoring at each stress level, whereas the conventional Type-II censoring is a special case. The proposed experimental scheme allows some extreme failures to be observed. The maximum likelihood estimators of the model parameters, the Fisher information, and asymptotic variance-covariance matrices of the maximum likelihood estimates are derived. We consider the optimal experimental planning problem by looking at four different optimality criteria. To avoid the computational burden in searching for the optimal allocation, a simple search procedure is suggested. Optimal allocation of units for two- and four-stress-level situations is determined numerically. The asymptotic Fisher information matrix and the asymptotic optimal allocation problem are also studied and the results are compared with optimal allocations with specified sample sizes. Finally, conclusions and some practical recommendations are provided.
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    Statistical Inference for Weibull Distribution Based on Competing Risk Data under Progressive Type-I Group Censoring
    (Selçuk Üniversitesi, 2015) Unal, Esra; Wu, Shou Jye; Bekci, Muhammet; Kinaci, Ismail; Kus, Coskun
    In this study, statistical inference is discussed for Weibull distribution based on competing risks data under progressive Type-I group censoring. The maximum likelihood procedure is used to get point estimates and asymptotic confidence intervals for unknown parameters. Some simulations results are presented. A numerical example is also provided.